For many of us, the 2016 League of Legends World Championship has left avid spectators suffering symptoms of withdrawal. For a few, thinking about TSM's or G2's disappointing run has left them experiencing lingering anxiety about whether or not the gap is really "closing." For others, post-worlds has left an almost incessant desire to learn more about the participating teams, players, and storylines.

While Worlds has ended and preseason underway, we can all agree that there is a lot left to digest - some in fact subconsciously recognized, but not consciously understood. What was the optimal meta game in which Worlds participants accrued incremental gold advantages? How did differing tower prioritization affect play patterns in acquiring neutral objectives, jungle monsters, and victories? Even if there are dozens of questions that can be asked, one statistic that can help us begin to pick at these questions is first mid tower rate.

----- What is First Mid Tower Rate? -----

First mid tower rate (FMTR) illustrates the percentage of games a given team has destroyed the mid-lane outer turret first. Consequentially, when a team's FMTR decreases, that means either 1) the team did not destroy their enemy mid-lane outer turret, or 2) the opposing team destroyed the mid-lane outer turret first. Inversely, teams with high FMTR end up destroying their opponent's mid-lane outer turret first. As a side note, FMTR is not equivalent to turret first blood; teams may acquire FMTR following turret first blood on a side turret. Furthermore, teams may also acquire FMTR even if their opponents destroyed a side turret first.

So why explore FMTR? Well, the outer mid-lane turret is often seen as one of the most important structures in the early to mid game. While up, pathing play patterns for invades are limited as mid-lane tower provides a source of vision in itself. Deep vision is also more contestable with tower support. Pathing for counter jungling and ganking is more predictable. In the context of postseason analysis, FMTR helps us read how teams capitalized their early game advantages and converted them into wins or the aforementioned play patterns (e.g. counter jungling, neutral objective control, etc.). Even beyond the World Championship, we can lightly use this data with appropriate context to pinpoint areas of improvement for teams as they approach Spring 2017.

----- Methodology -----

Throughout this article will be multiple graphs depicting the relationship between FMTR and related variables, including win rate, share of overall jungle monsters killed, and dragon rate. In this regard, we can make general assessments on the strategic play patterns of Worlds participants, what to expect for each team moving forward, and what you can do while on the Rift.

Every region is identified alphabetically with a different color in the color spectrum. Dark grey trend lines illustrate the general win rate for FMTR across all games played during the 2016 World Championship. Red lines on the other hand clarify the 50% mark for the assessed variables, helping us spatialize statistical trends with quadrants. In the end, supplementing the assessed graphs with trend lines and spatial quadrants will help identify statistical anomalies, laud teams who outperform their statistical counterparts, and reveal general win conditions for solo queue. To help read the upcoming graphs, Figure 1 illustrates how I will identify the quadrants and trend lines:

Figure 1. Quadrant Key

With the limited sample size, the 2016 World Championship FMTR graphs are susceptible to misinformation. While they do offer general instruction on how teams win games, statistics such as win rate will be somewhat flawed due to competitive irregularity (aka the Korean overlords dominating everyone but each other). As such, I highly recommend reading trends as general win conditions while reading outliers in a case by case basis with appropriate knowledge to match opponents (e.g. H2K not confronting a LCK team until the semifinals).

----- Push Mid for Success? -----
Part 1. Win Rate

Let's start with something simple: the correlation between win rate and FMTR during 2016 Worlds. By assessing the trend line, we can safely deduce that destroying mid tower first led to a higher probability of won games. This is indicated funnily enough by all (and only) the top four teams at 2016 Worlds residing in quadrant 1. On the other hand, as teams' FMTRs decreased, their win rates correspondingly decreased. With no teams inside quadrant 2 and quadrant 4, we should note that it is difficult to achieve an above aggregate 50% win rate with an under 50% FMTR (and vice versa). In other words, there was not a single team at 2016 Worlds that had an above 50% chance of winning the match when allowing their mid-lane tower to fall first. While not a crucial win condition, the numbers indicate that destroying mid-lane turret first contributed mightily to a team's overall win percentage.

Figure 2. Data provided by league-analytics.com

Some other interesting observations to note with the help of Figure 2:

A team's over-insistence on side lane priority as a primary win condition can be measured by the distance between their data point and the trend line. To present an example, greater side lane insistence translates into further distance from the FMTR trend line, indicating lesser mid-lane priority relative to win rate. Looking at Figure 2, we can assert that Chinese teams in particular did not see first mid-lane turret blood as a win condition during 2016 Worlds. Edward Gaming (EDG) for example was a uniquely resilient team during 2016 Worlds. Despite losing their mid-lane tower first roughly 75% of all their games, they proved to withstand unfavorable map pressure and secure a near 50% aggregate win rate through their side lanes (or maybe just bottom lane).

While H2K and ROX Tigers (ROX) had relatively the same win rate, H2K had a much higher FMTR (85% as opposed to 56%). In reading the differences lightly, we can claim that H2K was relatively reliant on acquiring tower advantages to secure their victories. ROX's true strength meanwhile is understated in this graph by their poor early game performances during the Group Stage. Because they fell victim to multiple losing lanes (e.g. a -707 average gold deficit at 10 minutes throughout the Group Stage), there were multiple instances where ROX had to dig themselves out of unfavorable map conditions.

----- Push Mid... What Can We Take Now? -----
Part 2. Share of Overall Jungle Monsters Killed

Okay, so we found a positive correlation between FMTR and win rate. What can we consequently extrapolate? Let's now explore how teams mobilized their mid-lane turret priority into other resource advantages. Figure 3 does just this by comparing 2016 Worlds participants' share of overall jungle monsters killed with their FMTR.

The aforementioned trend line, unlike Figure 2's trend line, helps us assess how teams 1) consume/protect their own jungle camps while 2) taking away their opponents' jungle camps. While we can use this graph as an indication of efficient jungling and counter jungling, we should remind ourselves that this statistic represents an entire team's effort to accrue or deny jungle camps.

Figure 3. Data provided by league-analytics.com

Some interesting observations to note with the help of Figure 3:

All the teams who achieved an aggregate +50% share of overall jungle monsters killed were also in quadrant 1, meaning they also prioritized in achieving a +50% FMTR. Inversely, every team with an aggregate -50% share of overall jungle monsters had a -50% FMTR. What does this mean? While the enemy jungle can also be exploitable with side lane turret first blood, combining this with first mid-lane turret blood provides the best opportunity to net potential enemy jungle camp denial. Figure 4 illustrates this very concept for those in Blue side.

Figure 4. Jungle Priority with Red Side Outer Mid-Lane Turret and Outer Bottom Lane Turret Destroyed

To provide some context, Figure 2 showcases Blue side destroying mid-lane outer turret and bottom lane outer turret. With only the top lane turret still up, Red side's priority line in the opposite quadrant inches back from point 1 to point 2. With Red side's turret line now at point 2, Blue side now has priority over the right quadrant given proper vision accrual. All Blue side needs to do now in order to obtain a wider gold difference is consume at every opportunity the opponent's Wolves, Gromps, and Blue Buffs. When analysts describe League of Legends as a battle of attrition, these are the strategic play patterns that make it so.

Let's now examine the two statistical anomalies in Figure 3: EDG and H2K. Interestingly enough, the only team above the trend line in quadrant 3 is EDG. If there is anything to say about this team, it is that they were unusually resilient in maintaining a competitive share of jungle monsters despite losing their mid-lane turret more often than not. While the criticisms for Clearlove not generating definitive advantages pre-15 minutes are somewhat warranted (EDG had a -900 average gold difference at 15 minutes throughout their Worlds run), we can compliment Clearlove — and his team as a whole — for securing EDG's jungle, being incredibly efficient with jungle routes, and being opportune with counter jungling opportunities.

As for H2K, despite having one of the highest FMTRs out of all worlds participants (84.62%), they only accrued an aggregate 49% share of overall jungle monsters. This statistic alone speaks to the feast or famine nature of H2K's style of play; if Jankos' ganks (or minutes of loitering) do not have a high success rate, H2K will be susceptible to falling behind due to suboptimal jungle routes. In that same sentiment, when ahead with winning lanes, H2K does a below average job in having every player kill neutral monsters in the enemy jungle — including Jankos. While we cannot fault H2K for making a miraculous, if not lucky run, at 2016 Worlds, there are some strategic play patterns they can fine-tune in order to better capitalize their early game advantages.

----- Push Mid... What Can We Take Now? -----
Part 3. Dragon Rate

FMTR vs. Dragon rate may be the trickiest graph to extrapolate any definitive assessments on, mainly because there are always factors that result in map priority resets regardless of first (mid-lane) turret blood. Dragon rate is not a statistic measuring the total number of Drakes/Elemental Dragons a team acquires, but rather the ratio of Drakes they acquire versus the Drakes they give up. As such, with just one poor team fight, player misallocation, or turret for neutral objective trade, a team's dragon rate can be underestimated, hiding their actual potency in securing neutral objectives. To read Figure 5, it is best not to judge the somewhat dubious dragon rate statistics, but the resulting trend line and quadrant allocations. By rereading the individual statistics as two-dimensional relationships, we can uncover some rather enlightening and accurate conclusions on Drake priority during 2016 Worlds.

Figure 5. Data provided by league-analytics.com

For teams above the trend line, the distance between themselves and the trend line measures their over-insistence in securing Drakes. Over-insistence isn't necessarily bad; it is an indication of a team's strategic adaptability in resetting map priority when behind and above-average neutral objective control. Inversely, for teams below the trend line, the distance between themselves and the trend line measures either 1) their willingness to give up Drakes, or 2) their inability to snowball first mid-lane turret blood into further Drakes. For example, relative to other teams with the same FMTR, G2 Esports (G2) did a below average job in capitalizing Drakes during 2016 Worlds. Samsung Galaxy (SSG) on the other hand is one of the teams with the highest insistence on acquiring drakes relative to their FMTR. Figure 6 presents hypothetical vision accrual and denial in order to secure drake and/or initiate a fog-of-war team fight.

Figure 6. Blue Side Dragon Pit Priority with Red Side Outer Mid-Lane Turret and Outer Bottom Lane Turret Destroyed

Since we are focused on FMTR, Figure 6 illustrates Blue side's potential priority as a result of destroying two outer turrets. When setting up Dragon pit priority, teams should look to extend their ring of vision as they acquire priority, whether it be from winning lanes, destroyed towers, and/or improper enemy lane allocation. With proper vision control inside the top right quadrant, Red side will have trouble regaining priority unless blue side misallocates players away from the Dragon pit. If Blue side is able to maintain extended periods of jungle priority, attrition will result through multiple Drakes, multiple opportunities to counter jungle, and an increasingly insurmountable gold advantage.

One last observation: it is worth noting that Albus Nox Luna (ANX) is the only team in quadrant 3. In their anomalous run at Worlds, ANX defied everyone's expectations by sneaking Drakes, Barons, and Elemental Dragons throughout the Group Stage. If we observe and appreciate ANX's position in Figure 5, what was magical wasn't just the manner in which they secured neutral objectives, but the frequency in which they did it at. Despite giving up first mid-lane turret blood over 50% of the time, ANX was able to acquire over 50% of their available Drakes. This isn't just over-insistence; ANX in quadrant 3 indicates a manner of unpredictability, strategic ingenuity, and repeated duplicity.

----- Thinking Ahead -----

Because League of Legends is an ever-changing game, in its attempt to bring something new to the table, prior assumptions on optimal win conditions will always be challenged, reassessed, and even rebuked. Yes, we can use FMTR to take snapshots of team tendencies and areas for improvement. However, more than anything, we can build with statistics diagrams to assess how the game should be played. Even for casual players who may not care about slight nuances to the meta, just understanding whether or not a certain win condition is now outdated following a new patch or rework can help give them some sort of competitive edge for their next game.

Considering this, statistics can only do so much for the average player. Unless there are stark anomalies that pose major red flags, optimal play patterns come only after players understand fundamental mechanics to the game. But at the same time, when matches are down to the wire, understanding how to manipulate the map to your benefit is one of the best ways to consistently improve your play. Mechanical outplays occur in all tiers — what you can do to set yourself apart from players in your skill range is thinking about how you can continually use the map to press your team's advantages.

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